Applied AI Engineer - Silicon Co-Design Group

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. 

NVIDIA's Silicon Co-Design Group is seeking an Applied AI Engineer to innovate, develop, and integrate innovative AI solutions into the design and automation infrastructure that powers our chips. Every CPU, GPU, and Tegra SoC NVIDIA has shipped in the past four years passed through our toolchain on its way to production — over 200 product SKUs were optimized during the Blackwell generation alone. Now we're rebuilding that toolchain around AI, and we're looking for the engineer to lead that charge. In this role, you will architect and implement solutions that enhance the efficiency, scalability, and intelligence of our workflows, driving initiatives from concept to deployment. If you combine deep technical expertise with a hands-on approach and an aim to push the boundaries of what's possible, this is your opportunity. At NVIDIA, we strive for perfection, encourage innovation, and provide opportunities to explore new ways to succeed! 

What you'll be doing: 

• Designing and implementing AI/LLM-powered systems to improve post-silicon validation, automation, and workflow efficiency within semiconductor validation environments. 

• Collaborating with multi-functional engineering teams to find opportunities for AI integration and performance optimization. 

• Evaluating emerging frameworks, architectures, and tools to improve efficiencies powered by artificial intelligence across the organization. 

• Establish and maintain data-driven indicators to quantify AI impact, identify performance gaps, and drive continuous improvement across systems. 

What we need to see: 

• BS, MS, or PhD or equivalent experience in CS, EE, CE, or a related field, with 5+ years of hands-on experience building and deploying ML/AI systems or data-intensive backend services. 

• 2+ years of direct Applied AI experience independently owning an AI agent, LLM-powered workflow, or intelligent automation system end-to-end — from prototype through production deployment. 

• Strong Python skills and proficiency in at least one static language such as C, C++, C#, Java, or Scala. 

• Demonstrated experience with deep learning frameworks like PyTorch or TensorFlow, and hands-on experience with agentic and orchestration tools including NeMo Agent Toolkit, LangChain, Semantic Kernel, AutoGen, CrewAI, or n8n. 

• Proven track record with deploying, monitoring, and debugging scalable AI/ML models. 

• Strong EE fundamentals, including computer architecture, high-speed interfaces, timing, power basics, and a solid understanding of firmware/driver structures and hardware interaction. 

• Ability to balance multiple simultaneous projects. 

• Excellent problem-solving, communication, and collaboration skills. 

Ways to stand out from the crowd: 

• Familiarity with modern AI technologies and methodologies for crafting and launching LLMs with ability to translate innovative AI research into practical, high-impact production tools. 

• Experience with building and deploying orchestration agents managing hundreds to thousands of tools. 

• Hands-on experience with silicon bring-up, characterization, or lab debug using standard tools (e.g., oscilloscopes, multimeters, logic analyzers). 

• Experience working within a silicon development environment, with exposure to chip and system characterization methodologies, process variation, statistical error rates, or advanced timing/power analysis. 

• Experience debugging complex system-level issues involving HW/SW interactions, including leadership or ownership in driving root cause analysis of silicon or feature-level issues. 

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com